Regularizing class-wise predictions via self-knowledge distillation S Yun, J Park, K Lee, J Shin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 278 | 2020 |
Surf: Semi-supervised reward learning with data augmentation for feedback-efficient preference-based reinforcement learning J Park, Y Seo, J Shin, H Lee, P Abbeel, K Lee arXiv preprint arXiv:2203.10050, 2022 | 59 | 2022 |
Opencos: Contrastive semi-supervised learning for handling open-set unlabeled data J Park, S Yun, J Jeong, J Shin European Conference on Computer Vision, 134-149, 2022 | 29 | 2022 |
Preference transformer: Modeling human preferences using transformers for rl C Kim, J Park, J Shin, H Lee, P Abbeel, K Lee arXiv preprint arXiv:2303.00957, 2023 | 27 | 2023 |
Object-aware regularization for addressing causal confusion in imitation learning J Park, Y Seo, C Liu, L Zhao, T Qin, J Shin, TY Liu Advances in Neural Information Processing Systems 34, 3029-3042, 2021 | 17 | 2021 |
Meta-learning with self-improving momentum target J Tack, J Park, H Lee, J Lee, J Shin Advances in Neural Information Processing Systems 35, 6318-6332, 2022 | 6 | 2022 |